Stage 1
Approach: For this module, I wanted to focus on understanding how the square footage of each level could be used for different purposes and different layouts. In other words, what is the building’s purpose for existing in the interior? My idea was to make it part hotel part art space/gallery. So, my custom nodes looked at combining two evaluation metrics stemming from floor areas. The first shows the number of private hotel rooms available, while the second dictates the square footage that is dedicated to art from across the globe.
Custom Node Logic 1: Building.numPrivateHotelRooms
(The higher you go, the larger the rooms. ¾ of the space of each level is designated to rooms while the remaining fourth is dedicated to common spaces.)
Custom Node Logic 2: Building.maxCommonSpaceArtSF
(The higher you go, the more space that is designated to global art. The 1/4 of each level area that is for left common spaces has another percentage dedicated to art for show and purchase.)
Combining both, we get the node BuildingEvaluatenumRoomandArtSF. The building form I chose was adapted from my Module 5 work, I call it the “Trophy Building Conceptual Mass” because of the shape. (see top of post)
The Stage 1 Summary Table:
24 combinations
Stage 2
Single-Objective Optimization Scheme Approach: For this module, the two evaluation metrics of number of rooms and common space art square footage were given unequal weight. The number of rooms was weighted twice as much as the latter. The reason for this was considering that those spaces that are currently dictated as a “room” could easily be changed into other experiential spaces as streams of revenue (restaurants, clubs, theaters, etc.) and general amenities. All options were calculated relative to each other (part to whole) and then summed in a ⅔ to ⅓ level of importance scheme to give a total score. Only the options that fit within the 2.5 - 3 million total square footage are evaluated for this part, the rest deleted. The gross floor areas, surface areas, and volume points were taken out for simplicity of viewing the table.
The Stage 2 Summary Table:
The top 3 alternatives are highlighted (Options M, O, and X) while the top choice I would recommend is additionally bolded. The reason I consider Option X is because based on the weighted scheme, we get the best of both worlds when it comes to the number of rooms available and the square footage to place art, when the former was more important. The option yielded the highest overall score.
Answers to Points to Ponder:
Q: Do the new evaluation metrics that you designed capture the meaningful differences between the building form alternatives?
A: The metrics do capture meaningful differences as the spread of results is distributed enough for me to examine and tell which combination of flexed parameters equate to a desired square footage in addition to a desired amount of rooms and space. Some other metrics I think would be interesting are those involving the solar potential in terms of the outer surface of the building and placing solar arrays there. Line of sight metrics would also be interesting in determining internal layout.
Q: What overall strategy do you feel best captures the relationship between the evaluation metrics?
A: The main thing to determine first is how to weigh each evaluation metric. Asking myself: what is the main purpose of the building, how does it function in the geographic location, and what could I compromise on? Then, figuring out how to illustrate that mathematically using some factor of normalization seemed to be an adaptable strategy.
Q: What propelled the recommended alternative to the top of the list?
A: Using the mathematical evaluation scheme, I was able to easily view which combination of flexed parameters scored the highest. You could easily tell just by ranking the scores highest to lowest which was the clear winner. The option I chose prioritized maximizing the number of rooms with a decent amount of space for art in common areas.